Abstract
•Key messageWe developed a dataset of the potential distribution of seven ecologically and economically important tree species of Europe in terms of their climatic suitability with an ensemble approach while accounting for uncertainty due to model algorithms. The dataset was documented following the ODMAP protocol to ensure reproducibility. Our maps are input data in a decision support tool “SusSelect” which predicts the vulnerability of forest trees in climate change and recommends adapted planting material. Dataset access is at https://doi.org/10.5281/zenodo.3686918. Associated metadata are available at https://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/fe79a36d-6db8-4a87-8a9f-c72a572b87e8.
Highlights
Climate change is likely to cause widespread shifts in the composition and range of plant communities worldwide (Scheffers et al 2016)
Species distribution models (SDMs), often referred to as ecological niche models (ENMs), are the most widely used tools for this purpose (Sykes et al 1996; Zimmermann et al 2010; Guisan et al 2013; Dyderski et al 2018), because they predict the potential distribution of species by exploiting the correlation between the known occurrence of a species and corresponding environmental conditions
Zurell et al (2020) proposed a reporting protocol known as ODMAP (Overview, Data, Model, Assessment, and Prediction), which offers a standardized way of communicating the results/outputs from SDMs by describing the objectives, model assumptions, scaling issues, data sources, model workflow, model predictions, and uncertainty
Summary
Climate change is likely to cause widespread shifts in the composition and range of plant communities worldwide (Scheffers et al 2016). SDMs have evolved and were applied for a wide range of questions such as to predict species range in the future (Sykes et al 1996; Thuiller et al 2008; Dyderski et al 2018), to test hypotheses about species distribution limits (Kreyling et al 2015), to develop conservation and management strategies in climate change (Guisan et al 2013; Hamann and Aitken 2013; Mcshea 2014; Schueler et al 2014), and understand the role of genetic variation in tree species distributions SDMs have evolved and were applied for a wide range of questions such as to predict species range in the future (Sykes et al 1996; Thuiller et al 2008; Dyderski et al 2018), to test hypotheses about species distribution limits (Kreyling et al 2015), to develop conservation and management strategies in climate change (Guisan et al 2013; Hamann and Aitken 2013; Mcshea 2014; Schueler et al 2014), and understand the role of genetic variation in tree species distributions (O’Neill et al. Vol.:(0123456789)
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